JN0-452 Mist AI Wireless - Specialist (JNCIS-MistAI-Wireless) Questions and Answers

When deploying three WLAN 2.4 GHz networks in your US-based site while ensuring that each network frequency is unique and does not overlap with other frequency channels, you should use OFDM channels 1, 6 and 11. So the correct answers are B.1, D.6, and A.11.

In Juniper Networks Mist AI Wireless, Service Level Expectations (SLEs) are used to measure and assure real user experience across the wireless network. Each SLE is built on specific classifiers, which break down failures into root causes such as DHCP, DNS, authentication, RF conditions, or application issues. Understanding which SLEs rely on DHCP classification is essential for accurate troubleshooting.

The two Wireless Assurance SLEs that include a DHCP classifier are Successful Connects and Time to Connect.

The Successful Connects SLE measures whether client devices are able to complete the full connection process successfully. This process includes association, authentication, and critically, DHCP address assignment. If a client fails to obtain an IP address, the connection is considered unsuccessful, and the failure is explicitly classified as a DHCP issue within this SLE.

The Time to Connect SLE measures how long it takes for a client to connect from the moment it initiates association until it is fully usable on the network. One of the key components of this timeline is the DHCP transaction time. Slow DHCP responses, retransmissions, or server delays directly increase the overall connection time, and Mist classifies these delays under DHCP within the Time to Connect SLE.

The other options are incorrect for the following reasons:

Roaming SLE focuses on re-association, authentication, and mobility events, not DHCP, since IP addressing is typically retained during roaming.

Coverage SLE evaluates RF signal strength, SNR, and cell overlap, with no dependency on DHCP.

Throughput SLE measures data transfer performance after connectivity is established and does not analyze DHCP behavior.

Therefore, the correct answer is Successful Connects and Time to Connect, as both SLEs directly depend on and classify DHCP-related performance and failures within Mist Wireless Assurance.

According to the Virtual Network Assistant | Juniper Networks US document2, Time to Connect is a Wireless Assurance SLE that has classifiers of Association, Authorization, DHCP, and Internet Services. This SLE measures how long it takes for a client device to connect to the network and access internet services.

According to the Cisco Catalyst 9800 Series Wireless Controller Software Configuration Guide1, there are two ways to access Marvis, which is a virtual network assistant that provides insights and troubleshooting for wireless networks:

Use the conversational assistant, which allows you to ask natural language questions and get answers from Marvis.

Use Actions, which are predefined queries that you can select from a list and get results from Marvis.

According to the Wi-Fi - Radio Modulation - TutorialsPoint document1, 64 QAM is a modulation method that will result in the highest theoretical data rates among the given options. 64 QAM uses both phase and amplitude modulation to encode six bits of information into each transmitted symbol. It can achieve up to 54 Mbps in the 802.11a and g systems.

The Compatible WLAN data rate setting is required for legacy 2.4 GHz scanners to connect to the WLAN.

According to the Data Rates - Mist document4, the WLAN data rate setting that is required for legacy 2.4 GHz scanners to connect to the WLAN is Compatible. This setting enables all data rates from 1 Mbps to 54 Mbps for both 2.4 GHz and 5 GHz bands. This setting is recommended for legacy devices that need low data rates to connect.

Two correct statements about Juniper Mist Dynamic Packet Capture are that no configuration is necessary for Mist’s Dynamic Packet Capture and it is automatically attached to a client event displayed on the Insights page. So the correct answers are A. No configuration is necessary for Mist’s Dynamic Packet Capture and B. It is automatically attached to a client event displayed on the Insights page.

 The AP Offline Marvis Action will consider all APs assigned to sites that have connected to the cloud previously for inclusion. So the correct answer is A. all APs assigned to sites that have connected to the cloud previously.

In a Juniper Mist environment, the Radio Resource Management (RRM) system is responsible for the automated allocation of channels and transmit power across all Access Points (APs) at a site. When you modify an RF Template—for example, by excluding specific UNII-2 Extended channels that certain legacy or region-specific clients cannot "see" or support—you are updating the intended policy for the network. However, because Mist RRM is designed for stability, it does not always force an immediate, disruptive channel change across the entire site the moment a template is saved.

To force the Mist AI engine to immediately recalculate the channel plan based on your new constraints and push those settings to the APs, you use the Optimize Now button. This feature is found within the Radio Management section of the site settings or the RF template application page. When "Optimize Now" is triggered, the Mist Cloud analyzes the current RF environment, takes your new channel exclusions into account, and issues a command to the APs to switch to the most efficient channels available within the newly defined subset.

Choosing Restart the APs (C) or Restart the WLANs (B) is unnecessary and causes more downtime than required. A reboot might eventually result in a new channel selection, but it does not guarantee that the RRM algorithm has fully processed the global optimization for the site. Restarting clients (D) does nothing to change the AP's channel behavior. By using Optimize Now (A), you ensure a coordinated, AI-driven transition that minimizes "co-channel interference" while respecting the updated frequency constraints you defined to accommodate your specific client devices. This ensures that clients previously struggling with unsupported UNII-2 channels are immediately moved to compatible frequencies.

In Juniper Networks Mist AI Wireless, access points discover upstream switch and port information using Link Layer Discovery Protocol (LLDP). LLDP is an IEEE-standard, vendor-neutral Layer 2 discovery protocol designed specifically to allow network devices to advertise and learn information about directly connected neighbors.

When a Juniper Mist AP connects to a wired switch, it uses LLDP to exchange information such as:

Switch hostname and chassis ID

Switch port identifier

VLAN details

Power over Ethernet (PoE) capabilities and power allocation

This information is critical for Mist operations and visibility. It enables the Mist cloud to accurately display AP-to-switch mappings, identify the exact switch port an AP is connected to, validate PoE delivery, and assist with troubleshooting wired-side issues that impact wireless performance. LLDP data is also leveraged by Mist AI and Marvis to correlate wired and wireless events, improving root-cause analysis.

The other options are incorrect for the following reasons:

CDP (Cisco Discovery Protocol) is a Cisco-proprietary protocol and is not used by Juniper Mist APs for switch discovery.

ARP (Address Resolution Protocol) resolves IP addresses to MAC addresses and does not provide device or port identity information.

SNMP is a management and monitoring protocol used by controllers or management systems, not by APs for neighbor discovery.

Because LLDP is standards-based, lightweight, and designed for neighbor discovery, it is the correct and supported protocol used by Juniper Mist APs to learn switch information.

Therefore, the correct answer is D. LLDP.

In 802.11 wireless networking and the Juniper Mist ecosystem, Passive Scanning is one of the two primary methods a client station (STA) uses to discover available wireless networks.4 In this mode, the client radio does not transmit any data to find an Access Point. Instead, it "waits and listens" on each supported channel for a specific period of time to hear Beacon Frames.5

Beacons are management frames sent periodically by an AP (typically every 100ms) to announce the presence and capabilities of a Basic Service Set (BSS).6 These frames contain critical information such as the SSID (Network Name), supported data rates, security protocols (RSN), and PHY requirements.7 Because the client only needs to keep its receiver active and does not have to power up its transmitter to send probe requests, passive scanning is significantly more power-efficient than active scanning, making it ideal for battery-constrained IoT devices.

However, the trade-off for this power efficiency is time. Since a client must stay on each channel long enough to guarantee it hears a beacon (at least one full beacon interval), scanning the entire 2.4 GHz, 5 GHz, and 6 GHz spectrum can take several seconds. In contrast, Active Scanning (options B, C, and D) involves the client sending Probe Requests (either wildcard/null or directed to a specific SSID) and waiting for a much shorter period for a Probe Response.8

From a Mist AI perspective, the dedicated scanning radio in Mist APs (like the AP43/AP45) performs its own version of passive and active scanning to build a complete map of the RF environment. This data is used by Marvis to detect "Neighbor" and "Honeypot" APs. While most modern mobile clients prefer active scanning to speed up the discovery and roaming process, passive scanning remains a fundamental requirement—especially on DFS channels where regulatory rules prohibit a client from transmitting until it has first "listened" to confirm no radar is present.

In Juniper Networks Mist AI Wireless, accurate location-based services (LBS) depend heavily on proper RF design and access point density. Juniper recommends that devices participating in Mist LBS maintain line-of-sight (LoS) to at least three access points to achieve reliable and consistent location accuracy.

Mist location services use advanced techniques such as RSSI triangulation, virtual BLE (vBLE), and AI-driven probability surface modeling to calculate a device’s position. These algorithms require multiple independent signal measurements to accurately determine a device’s X,Y coordinates. With signals received from three or more APs, Mist can triangulate the device position effectively and minimize errors caused by multipath reflections, attenuation, or transient RF noise.

If a device has line-of-sight to only one or two APs, the system lacks sufficient spatial diversity to calculate a precise location. This can result in ambiguous positioning, reduced accuracy, or excessive location “drift.” While additional APs (four or more) can further improve accuracy and stability—especially in high-value use cases such as asset tracking or wayfinding—three APs is the recommended minimum baseline for dependable LBS performance.

Mist’s AI continuously evaluates signal quality, AP geometry, and environmental factors to refine location estimates, but it cannot compensate for insufficient AP visibility. As a result, Juniper best practices for LBS design emphasize:

Proper AP placement and height

Adequate AP density

Ensuring devices can “see” at least three APs at all times

The other options are incorrect because:

One or two APs do not provide enough data for reliable triangulation.

Four APs may improve accuracy but are not the minimum recommendation.

Therefore, the correct answer is B. 3.

In Juniper Networks Mist AI Wireless, understanding modulation schemes is essential for designing and operating high-performance Wi-Fi 6 (802.11ax) networks. Modulation directly affects how much data can be transmitted per symbol, and therefore determines the maximum achievable data rates under optimal RF conditions.

802.11ax introduces 1024-QAM (Quadrature Amplitude Modulation) as its highest supported modulation scheme. With 1024-QAM, each symbol encodes 10 bits of data, which represents a significant increase compared to earlier standards. For reference:

64-QAM (used in earlier standards) carries 6 bits per symbol

256-QAM (introduced in 802.11ac) carries 8 bits per symbol

1024-QAM increases this to 10 bits per symbol

This higher bit density allows Wi-Fi 6 devices to achieve higher peak throughput, especially in environments with excellent signal quality. However, 1024-QAM requires very high Signal-to-Noise Ratio (SNR) and low interference to function reliably. As a result, it is typically achieved only when clients are close to the access point and RF conditions are clean.

Mist AI Wireless continuously monitors client RSSI, SNR, retransmissions, and modulation rates through advanced telemetry. Using this data, Mist can determine whether clients are successfully operating at higher modulation levels like 1024-QAM or are falling back to lower schemes due to RF impairments. This insight directly feeds into SLEs and AI-driven recommendations for RF tuning, AP placement, and channel planning.

The incorrect options are explained as follows:

64-QAM and 256-QAM are valid modulation schemes but do not provide the highest data rates in 802.11ax.

4096-QAM is not supported by the 802.11ax standard and is therefore invalid.

Thus, 1024-QAM is the modulation scheme that provides the highest data rate level for 802.11ax devices.

According to the exhibit, the WLAN has a minimum basic rate of 24 Mbps for both 2.4 GHz and 5 GHz bands. This corresponds to the high-density data rate setting in Mist, which disables all data rates below 24 Mbps. This setting is recommended for high density designs, where clients have enough signal strength and quality to operate at higher rates.

According to the Cisco Catalyst 9800 Series Wireless Controller Software Configuration Guide2, a non-compliant AP is an AP that has a different hardware model than what is expected by the cloud configuration. This can happen when an AP is replaced with an incorrect model or when an AP is moved to a different site group that has a different hardware model requirement. The solution is to replace the AP with the correct hardware model.

 According to the Data Rates - Mist document1, a honeypot AP is an AP that is not associated with your network, but broadcasts your corporate login page and WLAN name. This is a type of rogue AP that tries to trick users into connecting to it and revealing their credentials or other sensitive information.

 According to the Cisco Catalyst 9800 Series Wireless Controller Software Configuration Guide1, RF templates are assigned to sites, which are logical groupings of devices based on physical location or other criteria. RF templates allow you to configure RF parameters such as channel width, transmit power, and data rates for multiple devices at once.

In a traditional wireless environment, verifying the functionality of network services like DHCP, DNS, or captive portals requires a physical presence at the site or an active client to report telemetry. However, the Marvis Minis feature within the Juniper Mist AI ecosystem is specifically designed to solve the problem of "empty site" verification. Marvis Minis act as Digital Twins—virtualized client agents that reside directly on the Mist Access Points (APs).

Because they are integrated into the AP firmware, Marvis Minis can simulate client behavior without requiring any actual user devices to be connected to the WLAN. When an administrator wants to verify that DHCP is working on a specific SSID, Marvis Minis perform automated "synthetic testing." The virtual client will attempt to associate with the WLAN, complete the 802.11 authentication/association process, and then request an IP address via DHCP. If the DHCP server is unreachable, the pool is exhausted, or the response is too slow, Marvis Minis will detect this failure and report it to the Mist Cloud.

This proactive validation is part of Mist’s "Always-On" network testing strategy. While Marvis Actions (D) would eventually report a DHCP failure once real clients started failing, and Marvis Query Language (C) could be used to search for historical failures, only Marvis Minis (B) can actively test and verify the service in a scenario where there are currently no clients. This allows engineers to identify and fix "sleeping" issues—such as a misconfigured VLAN on a switch port or a downed DHCP server—before the first user even walks into the building, ensuring a "validated" network state at all times.

In the Juniper Mist dashboard, the Marvis Actions page serves as a centralized "proactive inbox" that identifies critical issues across the organization. However, the depth of information and the ability to interact with these findings are strictly tied to the Marvis Virtual Network Assistant (VNA) subscription.

The Mist dashboard provides a basic level of visibility even without a full Marvis license, allowing administrators to see that certain high-level categories (such as AP, Switch, or Gateway) have identified issues. This is designed to demonstrate the value of the AI engine. However, when you see a lock symbol next to sub-categories or specific Marvis Actions, it indicates that the organizational account does not have an active Marvis VNA subscription for those specific devices.

Without the subscription, the system will not permit the user to "drill down" into the root cause analysis, view historical event timelines, or access the specific remediation steps suggested by the AI. For example, while a standard Wi-Fi Assurance license might show that an AP is offline, the Marvis VNA subscription is what enables the detailed investigation—such as determining if the offline status is due to a cable failure, a bad PoE port on a switch, or a firmware mismatch.

To unlock these features and remove the lock symbols, a SUB-VNA (Virtual Network Assistant) subscription must be applied to the access points in the site. Once licensed, Marvis can provide full "conversational AI" capabilities, allowing you to ask natural language questions about the APs and giving you the interactive tools needed to resolve the issues identified in the Actions dashboard. Therefore, the presence of the lock icon is a direct indicator of a missing or expired subscription tier required for advanced AI-driven troubleshooting.

In Juniper Networks Mist AI Wireless, a rogue access point (AP) is precisely defined to avoid confusion with external or non-threatening wireless devices. Mist qualifies a rogue AP as an unauthorized access point that is physically connected to your wired network infrastructure.

This distinction is critical from a security perspective. A rogue AP represents a direct threat because it bypasses established security controls by providing wireless access into the enterprise wired network without authorization. Such APs are often installed by users without IT approval or, in more serious cases, by malicious actors attempting to gain internal network access.

Mist APs continuously scan the RF environment and correlate wireless observations with wired-side intelligence. If an AP is detected advertising SSIDs and Mist can confirm—through MAC address correlation and wired discovery—that the device is connected to the enterprise’s wired network but is not claimed or authorized in the Mist cloud, it is classified as a rogue AP. This allows administrators to take immediate remediation actions, such as physical removal or switch-port shutdown.

The other options are incorrect for the following reasons:

Neighbor APs are access points belonging to nearby organizations or environments and are not security threats by default. Mist classifies these separately for RF awareness.

APs close to your network as measured by RSSI may simply be physically nearby but not connected to your infrastructure; proximity alone does not make an AP rogue.

Honeypot APs are intentionally deployed decoy access points used in security research or attack detection and are not Mist’s definition of a rogue AP.

Therefore, Mist correctly defines a rogue AP as an unauthorized AP connected to your wired network, making option A the correct answer.

When using location-based services (LBS) at a new warehouse and placing APs on the floor plan with correct scale while ensuring correct location accuracy in this scenario where APs are mounted on trusses 14 feet (4.3 meters) from floor, two actions that should be taken are installing Virtual Beacons in each aisle and configuring height of each AP. So the correct answers are A. Install Virtual Beacons in each aisle and B. Configure height of each AP.

According to the exhibit, the organization has a total of two licenses for Marvis wireless, and one of them is in use. Therefore, the organization has one available license and one used license for Marvis wireless.

In Juniper Networks Mist AI Wireless, WxLAN policies are evaluated using a top-down, first-match logic. This means that when traffic matches a policy condition, that policy is applied immediately, and no further policies are evaluated. Understanding this evaluation order is critical when troubleshooting access discrepancies between user types such as BYOD and guest users.

From the scenario and the exhibit, guest devices are able to access youtube.com, while BYOD devices are blocked. This indicates that:

The guest WxLAN policy allows “All Video and Music” traffic (which includes YouTube).

The BYOD WxLAN policy blocks “All Video and Music” traffic.

The BYOD policy is evaluated before the guest policy.

Because BYOD users are matched to the BYOD label, their traffic hits the BYOD policy first and is denied before it can reach the more permissive guest policy. Simply modifying labels or deleting policies is unnecessary and could introduce unintended access control issues.

The correct and least disruptive solution is to move the BYOD WxLAN policy above the guest policy and then adjust the BYOD policy rules (for example, allowing YouTube or the “All Video and Music” category). By reordering the policies, you ensure that BYOD traffic is evaluated correctly and receives the intended permissions without impacting guest access.

The incorrect options are explained as follows:

Deleting policies (Options A and C) is not best practice and risks breaking segmentation and access control.

Option B is irrelevant, as the contractor policy does not affect BYOD or guest traffic in this scenario.

Therefore, the correct solution is to move the WxLAN policy for BYOD above the policy for guests, making Option D the correct answer.

The AI VALIDATED status update means that the issue was opened and Marvis confirms it has been closed.

According to the Marvis Virtual Network Assistant Datasheet1, the AI-VALIDATED status update means that the issue was opened and Marvis confirms it has been closed. This status indicates that Marvis has verified that the issue is no longer present and the root cause has been resolved.

Referring to the exhibit and considering that it is in the USA, the WLAN with SSID Eero1234 is not configured to industry best practices while the WLAN with SSID NETGEAR24 is configured to industry best practices.

According to the Mist documentation1, asset tracking is a service that allows you to find key assets and people with detailed analytics based on their location using Mist-supported third-party BLE beacons. To enable asset tracking, you need to configure both the BLE beacons and the Mist cloud settings.

The Show assets check box is a setting in Live View that allows you to display or hide the assets on the floor plan2. If this check box is not selected, you will not be able to see the third-party beacons on Live View.

The Locate this Client as an Asset check box is a setting at the BLE client level that allows you to treat a BLE client as an asset for location purposes3. If this check box is not selected, you will not be able to track the BLE client as an asset.

To review and troubleshoot the roaming activity of a specific client within a Juniper Mist environment, administrators rely on the conversational and analytical power of the Marvis Virtual Network Assistant (D) and its underlying Marvis Query Language (C). While other Marvis components like Actions focus on organization-wide health and Minis focus on synthetic testing, the VNA and MQL are specifically designed for deep-dive investigations into individual client experiences.

The Marvis Virtual Network Assistant (VNA) serves as the primary interface for this task. It allows an administrator to interact with the Mist AI using natural language. By typing a request such as "Troubleshoot client [Client Name]" or "How was the roaming for [Client Name]?", Marvis VNA aggregates all relevant telemetry data—including signal strength (RSSI), AP transitions, and authentication timings—into a simplified, human-readable summary. It provides a visual timeline of where the client moved and whether each roam was successful, slow, or failed.

Behind the scenes, these natural language requests are often converted into or powered by the Marvis Query Language (MQL). MQL is a structured way to query the Mist Graph API. For specific roaming reviews, the ROAMINGOF clause is used to filter the massive Mist data set for events related only to that client's mobility. For example, a query like roaming of "User-1" during last 24 hours will return a detailed data set showing the "From AP" and "To AP" details, the delta in signal strength during the handoff, and any associated latency.

By using these two features together, administrators can distinguish between a "sticky client" (one that refuses to roam despite a better signal being available) and a "coverage hole" (where the signal drops too low before a new AP is detected). This AI-driven approach eliminates the need for manual packet captures or log parsing, significantly reducing the Mean Time to Repair (MTTR) for mobility-related issues.

The exhibit shows a graph of the client’s roaming history over time. The x-axis represents the time and the y-axis represents the access point ID. Each dot on the graph indicates a roam event where the client switched from one access point to another.

The graph shows that the client roamed between different access points multiple times within a short period of time. This indicates that the client was experiencing frequent roams between different access points, which could affect its network performance and user experience.

According to Wikipedia1, 802.1X is an IEEE Standard for port-based network access control (PNAC). It provides an authentication mechanism to devices wishing to attach to a LAN or WLAN using Extensible Authentication Protocol (EAP) over wired IEEE 802 networks and over 802.11 wireless networks, which is known as “EAP over LAN” or EAPOL.

The authentication process involves three parties: a supplicant (the client device), an authenticator (the network device such as an access point), and an authentication server (typically a RADIUS server). The supplicant must provide valid credentials to the authenticator before it can access the network resources.

The credentials are exchanged with a RADIUS server prior to the 4-way Handshake because the 4-way Handshake is used to establish encryption keys between the supplicant and authenticator after successful authentication2. The credentials are exchanged with a RADIUS server after the 802.11 Association because the 802.11 Association is used to establish a logical link between the supplicant and authenticator before authentication can take place3.

In Juniper Networks Mist AI Wireless, controlling client connection quality is a critical part of maintaining high Service Level Expectations (SLEs). One of the most effective ways to ensure good user experience is by enforcing a minimum acceptable RSSI (Received Signal Strength Indication) threshold for client devices. This functionality is implemented using wireless traffic filtering at the WLAN level.

Wireless traffic filtering allows administrators to define minimum and maximum RSSI thresholds that determine whether a client is permitted to associate or remain connected to an SSID. If a client’s RSSI falls below the configured minimum threshold, the AP can deny association requests or deauthenticate the client. This prevents low-signal or “sticky” clients from connecting at poor signal levels, which would otherwise result in excessive retries, low data rates, increased airtime consumption, and degraded performance for all users.

Mist applies these controls intelligently and surfaces their impact through AI-driven analytics. When low-RSSI clients are filtered, Mist can correlate improvements in throughput, latency, and roaming behavior directly to RF health and client quality metrics. This aligns with Mist best practices, which emphasize proactive client quality enforcement rather than reactive troubleshooting.

The incorrect options are explained as follows:

WLAN forwarding determines how traffic is bridged, tunneled, or NATed and has no impact on RSSI enforcement.

Geofencing is used for location-based services and RTLS use cases, not RF signal quality control.

WLAN rate limit restricts bandwidth usage per client or SSID but does not evaluate or enforce signal strength requirements.

Therefore, the correct feature required to set an acceptable minimum RSSI for client devices is wireless traffic filtering, which directly controls association behavior based on signal quality and helps maintain optimal wireless performance.